Reconfiguring Strategic Capabilities in the Digital Era: How AI-Enabled Dynamic Capability, Data-Driven Culture, and Organizational Learning Shape Firm Performance

In the era of digital transformation, organizations increasingly invest in Artificial Intelligence (AI) to enhance competitiveness, yet persistent evidence shows that AI investment does not automatically translate into superior firm performance. Drawing on the Resource-Based View (RBV) and Dynamic Capabilities Theory (DCT), this study aims to explain this paradox by examining how AI-enabled dynamic capability (AIDC) is converted into performance outcomes through organizational mechanisms. Specifically, the study investigates the mediating roles of organizational data-driven culture (DDC) and organizational learning (OL). Data were collected from 254 senior managers and executives in U.S. firms actively employing AI technologies and analyzed using partial least squares structural equation modeling (PLS-SEM). The results indicate that AIDC exerts a significant direct effect on firm performance as well as indirect effects through both DDC and OL. Serial mediation analysis reveals that AIDC enhances performance by first fostering a data-driven mindset and subsequently institutionalizing learning processes that translate AI-generated insights into actionable organizational routines. Moreover, DDC plays a contingent moderating role in the AIDC–performance relationship, revealing a nonlinear effect whereby excessive reliance on data weakens the marginal performance benefits of AIDC. Taken together, these findings demonstrate the dual role of data-driven culture: while DDC functions as an enabling mediator that facilitates AI value creation, beyond a threshold it constrains dynamic reconfiguration by limiting managerial discretion and strategic flexibility. This insight exposes the “dark side” of data-driven culture and extends the RBV and DCT by introducing a boundary condition to the performance effects of AI-enabled capabilities. From a managerial perspective, the study highlights the importance of balancing analytical discipline with adaptive learning to sustain digital efficiency and strategic agility.